A Method for Uncertainty Elicitation of Experts Using Belief Function
The reliability of the biomedical data plays an essential role in the translation of the computational models and simulations of the human body systems into clinical decision support. Numerical models are commonly linked to the hypotheses on the data range of values due to the lack of in vivo data for some biomaterial variables. However, the reliability of these data is still not fully understood due to a lack of a systematic evaluation approach. The objective of this present study was to assess the reliability of biomedical data using expert judgment and belief theory. A systematic evaluation framework was developed using belief theory to perform the expert elicitation process. Seven parameters related to the muscle morphology and mechanics and motion analysis were selected. Twenty data sources related to these parameters were acquired using a systematic review process on the reliable search engines. A questionnaire was established including four main questions and four complementary questions related to the confidence levels. Eleven experts participated into the evaluation process via Google Form. A transformation process was developed to convert qualitative expert judgments to the numeric representations of the mass functions in the framework of belief theory. Two combination rules (Demspter and Dubois-Prade) were used to fuse the responses of multiple experts. At the end, data reliability was assessed using the pignistic probability to select the sources that correspond to some on-demand levels of confidence.
KeywordsBiomechanical data reliability Expert opinion Expert elicitation Belief theory
The authors would like to thank all anonymous experts participating into the evaluation process.
This work was carried out and funded in the framework of the Labex MS2T. It was supported by the French Government, through the program “Investments for the future” managed by the National Agency for Research (Reference ANR-11-IDEX-0004-02).
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